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The neighborhood social environment and physical activity: a systematic scoping review.

ABSTRACT: BACKGROUND:Investigating the association of the neighborhood social environment on physical activity is complex. A systematic scoping review was performed to (1) provide an inventory of studies assessing the influence of the neighborhood social environment on physical activity since 2006; (2) describe methodologies employed; and (3) formulate recommendations for the field. METHODS:Two databases were searched using terms related to 'physical activity,' 'neighborhood,' and 'social environment' in January 2017. Eligibility criteria included: 1) physical activity as an outcome; 2) neighborhood social environment as a predictor; 3) healthy population (without diagnosed clinical condition or special population); 4) observational or experimental design. Of 1352 studies identified, 181 were included. Textual data relevant to the social environment measurement and analysis were extracted from each article into qualitative software (MAXQDA) and coded to identify social environmental constructs, measurement methods, level of measurement (individual vs. aggregated to neighborhood), and whether authors explicitly recognized the construct as the social environment. The following measures were generated for each construct: number of unique measurements; % of times measured at an aggregate level; % of times authors referred to the construct as the social environment. Social environmental constructs were then grouped into larger descriptive dimensions. RESULTS/FINDINGS:Fifty-nine social environmental constructs were identified and grouped into 9 dimensions: Crime & Safety (n?=?133 studies; included in 73% of studies); Economic & Social Disadvantage (n?=?55, 33%); Social Cohesion & Capital (n?=?47, 26%); Social Relationships (n?=?22, 12%); Social Environment (n?=?16, 9%); Disorder & Incivilities (n?=?15, 8%); Sense of Place/Belonging (n?=?8, 4%); Discrimination/Segregation (n?=?3, 2%); Civic Participation & Engagement (n?=?2, 1%). Across all articles, the social environment was measured using 176 different methods, was measured at an aggregate-level 38% of the time, and referred to as the social environment 23% of the time. CONCLUSIONS:Inconsistent terminology, definitions, and measurement of the social environment and the lack of explicit language identifying constructs as the social environment make it challenging to compare results across studies and draw conclusions. Improvements are needed to increase our understanding of social environmental correlates and/or determinants of physical activity and facilitate cross-disciplinary conversations necessary to effectively intervene to promote physical activity. TRIAL REGISTRATION:PROSPERO CRD42017059580.

SUBMITTER: Kepper MM

PROVIDER: S-EPMC6902518 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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The neighborhood social environment and physical activity: a systematic scoping review.

Kepper Maura M MM Myers Candice A CA Denstel Kara D KD Hunter Ruth F RF Guan Win W Broyles Stephanie T ST

The international journal of behavioral nutrition and physical activity 20191209 1

<h4>Background</h4>Investigating the association of the neighborhood social environment on physical activity is complex. A systematic scoping review was performed to (1) provide an inventory of studies assessing the influence of the neighborhood social environment on physical activity since 2006; (2) describe methodologies employed; and (3) formulate recommendations for the field.<h4>Methods</h4>Two databases were searched using terms related to 'physical activity,' 'neighborhood,' and 'social e ...[more]

PMID: 31815626

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Project description:BACKGROUND:Smartphone apps promoting physical activity (PA) are abundant, but few produce substantial and sustained behavior change. Although many PA apps purport to induce users to compare themselves with others (by invoking social comparison processes), improvements in PA and other health behaviors are inconsistent. Existing literature suggests that social comparison may motivate PA for some people under some circumstances. However, 2 aspects of work that apply social comparison theory to PA apps remain unclear: (1) how comparison processes have been operationalized or harnessed in existing PA apps and (2) whether incorporating sources of variability in response to comparison have been used to tailor comparison features of apps, which could improve their effectiveness for promoting PA. OBJECTIVE:The aim of this meta-review was to summarize existing systematic, quantitative, and narrative reviews of behavior change techniques in PA apps, with an emphasis on social comparison features, to examine how social comparison is operationalized and implemented. METHODS:We searched PubMed, Web of Science, and PsycINFO for reviews of PA smartphone apps. Of the 3743 initial articles returned, 26 reviews met the inclusion criteria. Two independent raters extracted the data from these reviews, including the definition of social comparison used to categorize app features, the percentage of apps categorized as inducing comparison, specific features intended to induce comparison, and any mention of tailoring comparison features. For reference, these data were also extracted for related processes (such as behavioral modeling, norm referencing, and social networking). RESULTS:Of the included review articles, 31% (8/26) categorized app features as prompting social comparison. The majority of these employed Abraham and Michie's earliest definition of comparison, which differs from versions in later iterations of the same taxonomy. Very few reviews specified what dimension users were expected to compare (eg, steps, physical fitness) or which features of the apps were used to induce comparison (eg, leaderboards, message boards). No review referenced tailoring of comparison features. In contrast, 54% (14/26) reviews categorized features for prompting behavioral modeling and 31% (8/26) referenced tailoring app features for users' personal goals or preferences. CONCLUSIONS:The heterogeneity across reviews of PA apps and the absence of relevant information (eg, about dimensions or features relevant for comparison) create confusion about how to best harness social comparison to increase PA and its effectiveness in future research. No evidence was found that important findings from the broader social comparison literature (eg, that people have differing preferences for and responses to social comparison information) have been incorporated in the design of existing PA apps. Greater integration of the mobile health (mHealth) and social comparison literatures may improve the effectiveness of PA apps, thereby increasing the public health impact of these mHealth tools. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID):RR2-https://osf.io/nh4td/.

Project description:BackgroundRecent obesity prevention initiatives focus on healthy neighborhood design, but most research examines neighborhood food retail and physical activity (PA) environments in isolation. We estimated joint, interactive, and cumulative impacts of neighborhood food retail and PA environment characteristics on body mass index (BMI) throughout early adulthood.Methods and findingsWe used cohort data from the Coronary Artery Risk Development in Young Adults (CARDIA) Study [n=4,092; Year 7 (24-42 years, 1992-1993) followed over 5 exams through Year 25 (2010-2011); 12,921 person-exam observations], with linked time-varying geographic information system-derived neighborhood environment measures. Using regression with fixed effects for individuals, we modeled time-lagged BMI as a function of food and PA resource density (counts per population) and neighborhood development intensity (a composite density score). We controlled for neighborhood poverty, individual-level sociodemographics, and BMI in the prior exam; and included significant interactions between neighborhood measures and by sex. Using model coefficients, we simulated BMI reductions in response to single and combined neighborhood improvements. Simulated increase in supermarket density (from 25(th) to 75(th) percentile) predicted inter-exam reduction in BMI of 0.09 kg/m(2) [estimate (95% CI): -0.09 (-0.16, -0.02)]. Increasing commercial PA facility density predicted BMI reductions up to 0.22 kg/m(2) in men, with variation across other neighborhood features [estimate (95% CI) range: -0.14 (-0.29, 0.01) to -0.22 (-0.37, -0.08)]. Simultaneous increases in supermarket and commercial PA facility density predicted inter-exam BMI reductions up to 0.31 kg/m(2) in men [estimate (95% CI) range: -0.23 (-0.39, -0.06) to -0.31 (-0.47, -0.15)] but not women. Reduced fast food restaurant and convenience store density and increased public PA facility density and neighborhood development intensity did not predict reductions in BMI.ConclusionsFindings suggest that improvements in neighborhood food retail or PA environments may accumulate to reduce BMI, but some neighborhood changes may be less beneficial to women.

Project description:BackgroundA supportive environment is a key factor in addressing the issue of health among older adults. There is already sufficient evidence that objective and self-reported measures of the neighborhood environment should be taken into account as crucial components of active aging, as they have been shown to influence physical activity; particularly in people aged 60+. Thus, both could inform policies and practices that promote successful aging in place. An increasing number of studies meanwhile consider these exposures in analyzing their impact on physical activity in the elderly. However, there is a wide variety of definitions, measurements and methodological approaches, which complicates the process of obtaining comparable estimates of the effects and pooled results. The aim of this review was to identify and summarize these differences in order to emphasize methodological implications for future reviews and meta analyzes in this field and, thus, to create a sound basis for synthesized evidence.MethodsA systematic literature search across eight databases was conducted to identify peer-reviewed articles examining the association of objective and perceived measures of the neighborhood environment and objectively measured or self-reported physical activity in adults aged ≥ 60 years. Two authors independently screened the articles according to predefined eligibility criteria, extracted data, and assessed study quality. A qualitative synthesis of the findings is provided.ResultsOf the 2967 records retrieved, 35 studies met the inclusion criteria. Five categories of methodological approaches, numerous measurement instruments to assess the neighborhood environment and physical activity, as well as several clusters of definitions of neighborhood, were identified.ConclusionsThe strength of evidence of the associations of specific categories of environmental attributes with physical activity varies across measurement types of the outcome and exposures as well as the physical activity domain observed and the operationalization of neighborhood. The latter being of great importance for the targeted age group. In the light of this, future reviews should consider these variations and stratify their summaries according to the different approaches, measures and definitions. Further, underlying mechanisms should be explored.

Project description:BACKGROUND:The number of deaths per year attributed to non-communicable diseases is increasing in low- and middle-income countries, including Thailand. To facilitate the development of evidence-based public health programs and policies in Thailand, research on physical activity (PA) and sedentary behaviour (SB) is needed. The aims of this scoping review were to: (i) map all available evidence on PA and SB in Thailand; (ii) identify research gaps; and (iii) suggest directions for future research. METHODS:A systematic literature search was conducted through 10 bibliographic databases. Additional articles were identified through secondary searches of reference lists, websites of relevant Thai health organisations, Google, and Google Scholar. Studies written in Thai or English were screened independently by two authors and included if they presented quantitative or qualitative data relevant to public health research on PA and/or SB. RESULTS:Out of 25,007 screened articles, a total of 564 studies were included in the review. Most studies included PA only (80%), 6.7% included SB only, and 13.3% included both PA and SB. The most common research focus was correlates (58.9%), followed by outcomes of PA/SB (22.2%), prevalence of PA/SB (12.4%), and instrument validation (3.2%). Most PA/SB research was cross-sectional (69.3%), while interventions (19.7%) and longitudinal studies (2.8%) were less represented. Most studies (94%) used self-reports of PA/SB, and few (2.5%) used device-based measures. Both sexes were examined in most studies (82.5%). Adults were the main target population group (51.1%), followed by older adults (26.9%), adolescents (15.7%), and children (6.3%). Clinical populations were investigated in the context of PA/SB in a relatively large number of studies (15.3%), most frequently those with cardiovascular disease, diabetes, and hypertension (22%, 21%, and 21% respectively). CONCLUSIONS:The number of Thai papers on PA published per year has been increasing, indicating a growing interest in this research area. More studies using population-representative samples are needed, particularly among children and adolescents, and investigating SB as a health risk factor. To provide stronger evidence on determinants and outcomes of PA/SB, longitudinal studies using standardised measures of PA and SB are required.

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The neighborhood social environment and physical activity: a systematic scoping review.

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The neighborhood social environment and physical activity: a systematic scoping review.

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